{
 "metadata": {
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  },
  "orig_nbformat": 2,
  "kernelspec": {
   "name": "python3",
   "display_name": "Python 3.7.3 64-bit ('ml2': pyenv)"
  },
  "interpreter": {
   "hash": "8caa4319d59a734f94e739df6b594acde678ec5f2e3eb7152d087fc4a1992669"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2,
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "# LTL Synthesis Data"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "source": [
    "from ml2.ltl.ltl_syn import LTLSynData, LTLSynSplitData"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Load"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "source": [
    "split_data = LTLSynSplitData.load('scpa-2')"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stderr",
     "text": [
      "INFO:ml2.artifact:Found split_data scpa-2 locally\n",
      "INFO:ml2.ltl.ltl_syn.ltl_syn_data:Read in metadata\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Shuffle"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "source": [
    "split_data.shuffle()"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Plot Statistics"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "source": [
    "split_data.plot_stats(splits=['train', 'val', 'test'])"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stderr",
     "text": [
      "INFO:root:Maximal Variable Index statistics plotted to /Users/Frederik/ml2-storage/ltl-syn/scpa-2/stats/max_var_id.eps\n",
      "INFO:root:Number of Inputs statistics plotted to /Users/Frederik/ml2-storage/ltl-syn/scpa-2/stats/num_inputs.eps\n",
      "INFO:root:Number of Latches statistics plotted to /Users/Frederik/ml2-storage/ltl-syn/scpa-2/stats/max_num_latches.eps\n",
      "INFO:root:Number of Outputs statistics plotted to /Users/Frederik/ml2-storage/ltl-syn/scpa-2/stats/num_outputs.eps\n",
      "INFO:root:Number of AND Gates statistics plotted to /Users/Frederik/ml2-storage/ltl-syn/scpa-2/stats/num_and_gates.eps\n"
     ]
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {
      "needs_background": "light"
     }
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {
      "needs_background": "light"
     }
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {
      "needs_background": "light"
     }
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {
      "needs_background": "light"
     }
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ],
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYMAAAEICAYAAAC9E5gJAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8rg+JYAAAACXBIWXMAAAsTAAALEwEAmpwYAAAdLElEQVR4nO3de5hcVZ3u8e87CSCKkEAaDeloMhJFRAdCS+JlRoQhBOQYnKNzwqhEBHJGYQZBDxc9DxEYZobREeWo8UEIF0UDIg45TCBEBUWPCTQQbglIizjpcGsNFxEBA+/5Y682RVvdXelOd3XS7+d56mHXb69d9dvVZP9qr71qL9kmIiJGtz9rdgIREdF8KQYREZFiEBERKQYREUGKQUREkGIQERGkGMQWTtLFkv6pSe8tSRdJelzSzc3IIWJzSTGIzUrSg5Iek/SKmtgxkm5sYlpD5Z3AQUCr7f16ayRpf0mWdEqP+JQSX9oj/k1Jn63Z9kVJT5dHp6QrJL21r8QkbSvpdEn3SfqdpHWSrpU0q5Edk/QRST9ppG1sHVIMYiiMAU5odhKbStKYTdzktcCDtn/XT7t5wHrgyF7Wz5D09j62f8j2DsArgZnAvcBNkg7sY5srgTnlPccDU4EvAe/pJ9cYpVIMYih8DviUpHE9V9R8Gx5bE7tR0jFl+SOSfirpXElPSHpA0ttLfG0565jX42UnSFou6beSfiTptTWvvUdZt758S/7bmnUXS1ooaamk3wHvrpPvbpKWlO07JB1b4kcDFwBvK9/Yz6j3QZQzpPcDxwHTJLXVafZvwNm9fJZ/5Eqn7dPLe5/Ty3v+NdUZyxzbK20/Xx7X2T6hpt2pkn5RPrfVkt5X4m8Evlazb0+U+HaSPi/pvyQ9KulrkrYv6yZIuqb8zdZLuklSji9bkPyxYii0AzcCnxrg9jOAO4FdgG8Bi4G3ArsDHwK+LGmHmvYfBM4CJgCrgMvgjwfi5eU1dgXmAl+VtGfNtn9HdSB+JVCvW2Qx0AnsRnVQ/2dJB9i+EPh74Ge2d7C9oJd9+RvgaeA7wDKqs4Sevgq8vhzEG3UVML22O67GXwMrbXf28xq/AP4S2Ak4A/impIm21/DSfRtX2v8r8Hpgb6q/xSTg9LLuk1SfUwvwKuDTQO51swVJMYihcjrwD5JaBrDtL21fZPsF4HJgMnCm7edsXw88T3Uw6vaftn9s+zngM1TfaCcDh1F141xke4Pt24HvAh+o2fZq2z+1/aLtZ2uTKK/xDuAU28/aXkX1jby37p565gGXl335FjBX0jY92vyeqiBtyoXwhwAB4+qsmwA80v1E0s7lG/uTkv64j7a/Y/uhsu+XA/cDda99SBIwHzjR9nrbvwX+marAAvwBmAi81vYfbN/k3Phsi5JiEEPC9t3ANcCpA9j80Zrl35fX6xmrPTNYW/O+T1P1z+9G1ac/oxwInyjdHR8EXl1v2zp2A7oPfN1+RfWNuF+lmLybcqYCXA28jPr99hcAr5L03xp57ZKDgSfqrPsN1YEZgHLwHgfsC2xXk9+RklbVfDZ7URWSelqAlwO31rS/rsSh6hrsAK4vXXsD+btHE6UYxFBaABzLSw+e3RdbX14Tqz04D8Tk7oXSfbQz1TfntcCPbI+reexg+2M12/b17fUhYGdJr6yJvQZY12BeH6b6N/Z/JT0CPEBVDP6kq8j281RdNWdRfePvz/uA23q5eP0D4K2SWnvbuFxX+TpwPLBLKRZ317x3z8/l11RF+E01n+VO5cI2tn9r+5O2/xx4L3BSPxe4Y4RJMYghY7uDqpvnH2tiXVQH0w9JGiPpo8DrBvlWh0p6p6RtqQ6mK2yvpTozeb2kD0vapjzeWi6QNpL/WuD/Af8i6WWS3gIcDXyzwbzmUR3g9655/PeS7y512n+DqljMrvdiqkyStAA4hqpfvl7e1wM3AP8haYaqYabbUI1E6vYKqgN+V3nto6jODLo9CrSWzxTbL1IVj3Ml7Vq2mSTp4LJ8mKTdS3fSk8ALwIu9fzQx0qQYxFA7k+rAU+tY4H9RdWe8ieqAOxjfojoLWU/VFfIhqL6tArOo+rUfoupHP4earpIGHAFMKdt/D1hg+/v9bSRpJlU31VdsP1LzWELVnXJEz23KdYXTqc5sau0m6WmqC9G3AG8G9i8H/d68j6oYfpOqK+mXVF1kB5f3Wg38O/AzqgP/m4Gf1mz/Q+Ae4BFJvy6xU0ruKyQ9BXwfeENZN608f7q85ldt39BHfjHCKNd4IiIiZwYREZFiEBERKQYREUGKQUREAGP7bzIyTZgwwVOmTOl1/eq+fkpU7Dm5/zYREVuTW2+99de2/+TOAFtsMZgyZQrt7e29rt/npP5fo/0LmzGhiIgtgKRf1YunmygiIlIMIiIixSAiIkgxiIgINqEYlJuK3S7pmvL8QEm3lVvg/kTS7iW+naTLy6xQKyVNqXmN00r8vu4bXJX47BLryK1vIyKG36acGZwArKl5vhD4oO29qW4U9r9L/Gjgcdu7A+dSpuYrs0vNpbox2WyqGafGqJp39ivAIcCewBE9ZqKKiIgh1lAxKPdFfw/VBBzdDOxYlneiuqsjVJNwX1KWrwQOLLe1nQMsLrNV/ZLq7of7lUeH7QfKPd0Xl7YRETFMGv2dwReBk6nmie12DLBU0u+Bp9h4r/RJlNmjbG+Q9CTVXLaTgBU123eycdKTtT3iM+olIWk+1dR7vOY1r2kw9YiI6E+/ZwaSDgMes31rj1UnAofabgUuAob8J1y2z7fdZrutpWUgU+tGREQ9jZwZvAN4r6RDqWZh2lHSfwJ72F5Z2lxONR8qVLNYTQY6JY2l6kL6TU28Wysbpw/sLR4REcOg3zMD26fZbrU9heoC8A+p+vR3kvT60uwgNl5cXsLGOV7fD/zQ1Qw6S4C5ZbTRVKqZkW6mmrlpmqSpZYq9uaVtREQMkwHdm6hcCzgW+K6kF4HHgY+W1RcC35DUQTUN4dyyzT2SrgBWAxuA48o0f0g6HlgGjAEW2b5nEPsUERGbaIud9rKtrc2DvVHd7blRXUSMMpJutd3WM55fIEdERIpBRESkGEREBCkGERFBikFERJBiEBERpBhERAQpBhERQYpBRESQYhAREaQYREQEKQYREUGKQUREkGIQERGkGEREBCkGERFBikFERLAJxUDSGEm3S7qmPL9M0n2S7pa0SNI2JS5J50nqkHSnpOk1rzFP0v3lMa8mvq+ku8o250nS5tzJiIjo26acGZzAxknvAS4D9gDeDGwPHFPih1BNdj8NmA8sBJC0M7AAmAHsByyQNL5ssxA4tma72QPYl4iIGKCGioGkVuA9wAXdMdtLXQA3A61l1Rzg0rJqBTBO0kTgYGC57fW2HweWA7PLuh1tryivdSlw+Gbav4iIaECjZwZfBE4GXuy5onQPfRi4roQmAWtrmnSWWF/xzjrxPyFpvqR2Se1dXV0Nph4REf3ptxhIOgx4zPatvTT5KvBj2zdt1szqsH2+7TbbbS0tLUP9dhERo0YjZwbvAN4r6UFgMXCApG8CSFoAtAAn1bRfB0yued5aYn3FW+vEIyJimPRbDGyfZrvV9hRgLvBD2x+SdAzVdYAjbNd2Hy0BjiyjimYCT9p+GFgGzJI0vlw4ngUsK+uekjSzjCI6Erh6s+5lRET0aewgtv0a8CvgZ2Uk6FW2zwSWAocCHcAzwFEAttdLOgu4pWx/pu31ZfnjwMVUo5KuLY+IiBgmm1QMbN8I3FiW625bRgQd18u6RcCiOvF2YK9NySUiIjaf/AI5IiJSDCIiIsUgIiJIMYiICFIMIiKCFIOIiCDFICIiSDGIiAhSDCIighSDiIggxSAiIkgxiIgIUgwiIoIUg4iIIMUgIiJIMYiICFIMIiKCBoqBpJdJulnSHZLukXRGiUvS2ZJ+LmmNpH+siZ8nqUPSnZKm17zWPEn3l8e8mvi+ku4q25xX5kKOiIhh0si0l88BB9h+WtI2wE8kXQu8EZgM7GH7RUm7lvaHANPKYwawEJghaWdgAdAGGLhV0hLbj5c2xwIrqeZQnk3mQY6IGDb9FoMyp/HT5ek25WHgY8Df2X6xtHustJkDXFq2WyFpnKSJwP7ActvrASQtB2ZLuhHY0faKEr8UOJwmFIN9Tuq/ze1fGPo8IiKGW0PXDCSNkbQKeIzqgL4SeB3wPyS1S7pW0rTSfBKwtmbzzhLrK95ZJ14vj/nl/dq7uroaST0iIhrQUDGw/YLtvYFWYD9JewHbAc/abgO+Diwasiw35nG+7TbbbS0tLUP9dhERo8YmjSay/QRwA1WffidwVVn1PeAtZXkd1bWEbq0l1le8tU48IiKGSSOjiVokjSvL2wMHAfcC/wG8uzR7F/DzsrwEOLKMKpoJPGn7YWAZMEvSeEnjgVnAsrLuKUkzyyiiI4GrN9cORkRE/xoZTTQRuETSGKricYXtayT9BLhM0olUF5iPKe2XAocCHcAzwFEAttdLOgu4pbQ7s/tiMvBx4GJge6oLxxlJFBExjBoZTXQnsE+d+BPAe+rEDRzXy2stos61BdvtwF79pxsREUMhv0COiIgUg4iISDGIiAhSDCIighSDiIggxSAiIkgxiIgIUgwiIoIUg4iIIMUgIiJIMYiICFIMIiKCFIOIiCDFICIiSDGIiAhSDCIighSDiIigsTmQXybpZkl3SLpH0hklPlXSSkkdki6XtG2Jb1eed5T1U2pe67QSv0/SwTXx2SXWIenUIdjPiIjoQyNnBs8BB9j+C2BvYHaZ6P4c4FzbuwOPA0eX9kcDj5f4uaUdkvYE5gJvAmYDX5U0psyt/BXgEGBP4IjSNiIihkm/xcCVp8vTbcrDwAHAlSV+CXB4WZ5TnlPWHyhJJb7Y9nO2fwl0APuVR4ftB2w/DywubSMiYpg0dM2gfINfBTwGLAd+ATxhe0Np0glMKsuTgLUAZf2TwC618R7b9Bavl8d8Se2S2ru6uhpJPSIiGtBQMbD9gu29gVaqb/J7DGVSfeRxvu02220tLS3NSCEiYqu0SaOJbD8B3AC8DRgnaWxZ1QqsK8vrgMkAZf1OwG9q4z226S0eERHDpJHRRC2SxpXl7YGDgDVUReH9pdk84OqyvKQ8p6z/oW2X+Nwy2mgqMA24GbgFmFZGJ21LdZF5yWbYt4iIaNDY/pswEbikjPr5M+AK29dIWg0slvRPwO3AhaX9hcA3JHUA66kO7ti+R9IVwGpgA3Cc7RcAJB0PLAPGAIts37PZ9jAiIvrVbzGwfSewT534A1TXD3rGnwU+0MtrnQ2cXSe+FFjaQL4RETEE8gvkiIhIMYiIiBSDiIggxSAiIkgxiIgIUgwiIoIUg4iIIMUgIiJIMYiICFIMIiKCFIOIiCDFICIiSDGIiAhSDCIighSDiIggxSAiIkgxiIgIGpsDebKkGyStlnSPpBN6rP+kJEuaUJ5L0nmSOiTdKWl6Tdt5ku4vj3k18X0l3VW2OU+SNudORkRE3xo5M9gAfNL2nsBM4DhJe0JVKIBZwH/VtD+EarL7acB8YGFpuzOwAJhBNV3mAknjyzYLgWNrtps9uN2KiIhN0W8xsP2w7dvK8m+BNcCksvpc4GTANZvMAS51ZQUwTtJE4GBgue31th8HlgOzy7odba+wbeBS4PDNs3sREdGITbpmIGkKsA+wUtIcYJ3tO3o0mwSsrXneWWJ9xTvrxOu9/3xJ7ZLau7q6NiX1iIjoQ8PFQNIOwHeBT1B1HX0aOH1o0qrP9vm222y3tbS0DOdbR0Rs1RoqBpK2oSoEl9m+CngdMBW4Q9KDQCtwm6RXA+uAyTWbt5ZYX/HWOvGIiBgmjYwmEnAhsMb2FwBs32V7V9tTbE+h6tqZbvsRYAlwZBlVNBN40vbDwDJglqTx5cLxLGBZWfeUpJnlvY4Erh6CfY2IiF6MbaDNO4APA3dJWlVin7a9tJf2S4FDgQ7gGeAoANvrJZ0F3FLanWl7fVn+OHAxsD1wbXlERMQw6bcY2P4J0Oe4/3J20L1s4Lhe2i0CFtWJtwN79ZdLREQMjUbODKIP+5zUf5vbvzD0eUREDEZuRxERESkGERGRYhAREaQYREQEKQYREUGKQUREkGIQERGkGEREBCkGERFBikFERJBiEBERpBhERAQpBhERQYpBRESQYhAREaQYREQEjc2BvEjSY5LurontLWmFpFWS2iXtV+KSdJ6kDkl3Sppes808SfeXx7ya+L6S7irbnFfmQY6IiGHUyExnFwNfBi6tif0bcIbtayUdWp7vDxwCTCuPGcBCYIaknYEFQBtg4FZJS2w/XtocC6ykmj95Nlv5HMiZHS0iRpp+zwxs/xhY3zMM7FiWdwIeKstzgEtdWQGMkzQROBhYbnt9KQDLgdll3Y62V5S5ky8FDh/sTkVExKYZ6BzInwCWSfo8VUF5e4lPAtbWtOsssb7inXXiERExjAZ6AfljwIm2JwMnAhduvpR6J2l+uUbR3tXVNRxvGRExKgy0GMwDrirL3wH2K8vrgMk17VpLrK94a514XbbPt91mu62lpWWAqUdERE8DLQYPAe8qywcA95flJcCRZVTRTOBJ2w8Dy4BZksZLGg/MApaVdU9JmllGER0JXD3QnYmIiIHp95qBpG9TjRSaIKmTalTQscCXJI0FngXml+ZLgUOBDuAZ4CgA2+slnQXcUtqdabv7ovTHqUYsbU81imirHkkUETES9VsMbB/Ry6p967Q1cFwvr7MIWFQn3g7s1V8eERExdPIL5IiISDGIiIgUg4iIIMUgIiJIMYiICFIMIiKCFIOIiCDFICIiSDGIiAhSDCIighSDiIggxSAiIhj4TGcxzDJvckQMpZwZREREikFERKQYREQEKQYREUEDxUDSIkmPSbq7JvY5SfdKulPS9ySNq1l3mqQOSfdJOrgmPrvEOiSdWhOfKmlliV8uadvNuH8REdGARkYTXQx8Gbi0JrYcOM32BknnAKcBp0jaE5gLvAnYDfi+pNeXbb4CHAR0ArdIWmJ7NXAOcK7txZK+BhwNLBz8ro1uGX0UEZui3zMD2z8G1veIXW97Q3m6Amgty3OAxbafs/1LoAPYrzw6bD9g+3lgMTBHkoADgCvL9pcAhw9ulyIiYlNtjt8ZfBS4vCxPoioO3TpLDGBtj/gMYBfgiZrCUts+hlnOJiJGr0FdQJb0GWADcNnmSaff95svqV1Se1dX13C8ZUTEqDDgMwNJHwEOAw607RJeB0yuadZaYvQS/w0wTtLYcnZQ2/5P2D4fOB+gra3NvbWL4ZOziYitw4DODCTNBk4G3mv7mZpVS4C5kraTNBWYBtwM3AJMKyOHtqW6yLykFJEbgPeX7ecBVw9sVyIiYqAaGVr6beBnwBskdUo6mmp00SuB5ZJWlVFA2L4HuAJYDVwHHGf7hfKt/3hgGbAGuKK0BTgFOElSB9U1hAs36x5GRES/+u0msn1EnXCvB2zbZwNn14kvBZbWiT9ANdooIiKaJL9AjoiIFIOIiEgxiIgIUgwiIoLMdBZNkN8mRIw8OTOIiIgUg4iISDdRbCHStRQxtHJmEBERKQYREZFiEBERpBhERAQpBhERQYpBRESQYhAREaQYREQE+dFZbMXyQ7WIxuXMICIiBlcMJI2TdKWkeyWtkfQ2STtLWi7p/vLf8aWtJJ0nqUPSnZKm17zOvNL+fknzBrtTERGxaQZ7ZvAl4DrbewB/QTXZ/anAD2xPA35QngMcAkwrj/nAQgBJOwMLgBlUcyEv6C4gERExPAZ8zUDSTsBfAR8BsP088LykOcD+pdklwI3AKcAc4FLbBlaUs4qJpe1y2+vL6y4HZgPfHmhuEQOV6wwxWg3mzGAq0AVcJOl2SRdIegXwKtsPlzaPAK8qy5OAtTXbd5ZYb/E/IWm+pHZJ7V1dXYNIPSIiag2mGIwFpgMLbe8D/I6NXUIAlLMAD+I9XsL2+bbbbLe1tLRsrpeNiBj1BjO0tBPotL2yPL+Sqhg8Kmmi7YdLN9BjZf06YHLN9q0lto6N3Urd8RsHkVfEsErXUmwNBnxmYPsRYK2kN5TQgcBqYAnQPSJoHnB1WV4CHFlGFc0EnizdScuAWZLGlwvHs0osIiKGyWB/dPYPwGWStgUeAI6iKjBXSDoa+BXwt6XtUuBQoAN4prTF9npJZwG3lHZndl9MjoiI4TGoYmB7FdBWZ9WBddoaOK6X11kELBpMLhFbinQrxUiUXyBHRETuTRSxJRius4mctYxeOTOIiIicGURsrfItPzZFzgwiIiLFICIi0k0UEYM0kO6odGGNPCkGEbFFSAEZWikGEbHVSgFpXIpBREQxmotHikFExCBsLQUko4kiIiLFICIiUgwiIoIUg4iIIMUgIiJIMYiICEbQ0FJJs4EvAWOAC2z/a5NTiogYEiNxOOqIODOQNAb4CnAIsCdwhKQ9m5tVRMToMSKKAbAf0GH7AdvPA4uBOU3OKSJi1FA1T32Tk5DeD8y2fUx5/mFghu3je7SbD8wvT98A3LeJbzUB+PUg0x0KIzUvGLm5jdS8ILkNxEjNC7a+3F5ru6VncMRcM2iE7fOB8we6vaR2222bMaXNYqTmBSM3t5GaFyS3gRipecHoyW2kdBOtAybXPG8tsYiIGAYjpRjcAkyTNFXStsBcYEmTc4qIGDVGRDeR7Q2SjgeWUQ0tXWT7niF4qwF3MQ2xkZoXjNzcRmpekNwGYqTmBaMktxFxATkiIpprpHQTRUREE6UYRETE6CgGkmZLuk9Sh6RTm51PN0kvk3SzpDsk3SPpjGbn1E3SOElXSrpX0hpJb2t2Tt0knSDp7vKZfaLJuSyS9Jiku2tinyuf252Svidp3AjJ67OS1klaVR6HDndefeS2t6QVJa92Sfs1Ia/Jkm6QtLr8v3VCiX+gPH9RUlOGmPaWW836T0qypAkDfhPbW/WD6oL0L4A/B7YF7gD2bHZeJTcBO5TlbYCVwMxm51XyuQQ4pixvC4xrdk4ll72Au4GXUw2A+D6wexPz+StgOnB3TWwWMLYsnwOcM0Ly+izwqRHwN6yX2/XAIWX5UODGJuQ1EZhell8J/Jzq9jhvpPqR641AW5M+s7q5leeTqQbf/AqYMND3GA1nBiP2VheuPF2eblMeTb+iL2knqn+wFwLYft72E01NaqM3AittP2N7A/Aj4G+alYztHwPre8SuL7kBrKD63UzT8xopesnNwI5leSfgoWFNCrD9sO3byvJvgTXAJNtrbG/q3Q6GJbey+lzgZAZ57BgNxWASsLbmeScbP8SmkzRG0irgMWC57ZVNTglgKtAFXCTpdkkXSHpFs5Mq7gb+UtIukl5O9S1ycj/bNNNHgWubnUSN40v31SJJ45udTI1PAJ+TtBb4PHBaM5ORNAXYh+psfUSpzU3SHGCd7TsG+7qjoRiMaLZfsL031bfH/STt1eSUoOp+mQ4stL0P8DtgRFxrsb2GquvleuA6YBXwQjNz6o2kzwAbgMuanUuxEHgdsDfwMPDvTc3mpT4GnGh7MnAi5ay0GSTtAHwX+ITtp5qVRz21uVH9v/Vp4PTN8dqjoRhsEbe6KN0wNwCzm5wKVGdPnTVnKVdSFYcRwfaFtve1/VfA41T9pyOKpI8AhwEfdOnYbTbbj5YvHy8CX6fqQh0p5gFXleXv0KTcJG1DdbC9zPZV/bUfTnVyex3VWfwdkh6kOrbdJunVA3n90VAMRuytLiS1dI80kbQ9cBBwb1OTAmw/AqyV9IYSOhBY3cSUXkLSruW/r6G6XvCt5mb0UmWippOB99p+ptn5dJM0sebp+6i63EaKh4B3leUDgPuHOwFJojojWWN7mKeW6Vu93GzfZXtX21NsT6H6Eje9/Pvd9PcYIV9ahlQZQvdFNt7q4uzmZlSR9BaqUTtjqArzFbbPbG5WFUl7AxdQjSR6ADjK9uNNTaqQdBOwC/AH4CTbP2hiLt8G9qe6lfCjwAKq/u7tgN+UZits//0IyGt/qi4iAw8C/9P2w8OZVx+53Uc10+FY4Fng47ZvHea83gncBNwFvFjCn6b6W/4foAV4Alhl++CRkJvtpTVtHqQa7TSg222PimIQERF9Gw3dRBER0Y8Ug4iISDGIiIgUg4iIIMUgIiJIMYiICFIMIiIC+P/ZKIBKHmWpQwAAAABJRU5ErkJggg=="
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Upload"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "source": [
    "LTLSynSplitData.upload('scpa-2', overwrite=False)"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Add to Weights and Biases"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "source": [
    "LTLSynSplitData.add_to_wandb('scpa-2', overwrite=False)"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stderr",
     "text": [
      "ERROR:wandb.jupyter:Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.\n",
      "INFO:ml2.artifact:Artifact scpa-2 has already been added to Weight and Biases\n",
      "INFO:ml2.artifact:If you would like to add the artifact as a new version set the overwrite to True\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Model Check"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "source": [
    "from ml2.ltl.ltl_syn.ltl_syn_data import model_check_data"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "model_check_data('scpa-2')"
   ],
   "outputs": [],
   "metadata": {}
  }
 ]
}